Correlation between gene methylation status and clinical features
Lung Adenocarcinoma (MOLECULAR_NONSMOKER)
07 February 2013  |  awg_luad__2013_02_07
Maintainer Information
Citation Information
doi:10.7908/C1BC3WNC
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between gene methylation status and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1BC3WNC
Overview
Introduction

This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.

Summary

Testing the association between 17281 genes and 14 clinical features across 62 samples, statistically thresholded by Q value < 0.05, 6 clinical features related to at least one genes.

  • 2 genes correlated to 'GENDER'.

    • RNASEH2C ,  KIF4B

  • 54 genes correlated to 'HISTOLOGICAL.TYPE'.

    • SPAG8 ,  IVD ,  TRPV1 ,  PITX3 ,  NOD2 ,  ...

  • 75 genes correlated to 'PATHOLOGICSPREAD(M)'.

    • LRRC8B ,  FBXO16 ,  NOTCH2 ,  ZNF563 ,  LRRC58 ,  ...

  • 52 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

    • UHRF1 ,  FBXO9 ,  DMXL1 ,  PPA1 ,  MYL6 ,  ...

  • 7 genes correlated to 'TOBACCOSMOKINGHISTORYINDICATOR'.

    • MT1H ,  SERPINE1 ,  WFDC10A ,  EXOC3L ,  FAM107A ,  ...

  • 1 gene correlated to 'YEAROFTOBACCOSMOKINGONSET'.

    • RNF123

  • No genes correlated to 'Time to Death', 'AGE', 'KARNOFSKY.PERFORMANCE.SCORE', 'PATHOLOGY.T', 'PATHOLOGY.N', 'TUMOR.STAGE', 'NUMBERPACKYEARSSMOKED', and 'STOPPEDSMOKINGYEAR'.

Results
Overview of the results

Complete statistical result table is provided in Supplement Table 1

Table 1.  Get Full Table This table shows the clinical features, statistical methods used, and the number of genes that are significantly associated with each clinical feature at Q value < 0.05.

Clinical feature Statistical test Significant genes Associated with                 Associated with
Time to Death Cox regression test   N=0        
AGE Spearman correlation test   N=0        
GENDER t test N=2 male N=1 female N=1
KARNOFSKY PERFORMANCE SCORE Spearman correlation test   N=0        
HISTOLOGICAL TYPE ANOVA test N=54        
PATHOLOGY T Spearman correlation test   N=0        
PATHOLOGY N Spearman correlation test   N=0        
PATHOLOGICSPREAD(M) ANOVA test N=75        
TUMOR STAGE Spearman correlation test   N=0        
RADIATIONS RADIATION REGIMENINDICATION t test N=52 yes N=21 no N=31
NUMBERPACKYEARSSMOKED Spearman correlation test   N=0        
STOPPEDSMOKINGYEAR Spearman correlation test   N=0        
TOBACCOSMOKINGHISTORYINDICATOR ANOVA test N=7        
YEAROFTOBACCOSMOKINGONSET Spearman correlation test N=1 higher yearoftobaccosmokingonset N=1 lower yearoftobaccosmokingonset N=0
Clinical variable #1: 'Time to Death'

No gene related to 'Time to Death'.

Table S1.  Basic characteristics of clinical feature: 'Time to Death'

Time to Death Duration (Months) 0.1-224 (median=12.7)
  censored N = 36
  death N = 15
     
  Significant markers N = 0
Clinical variable #2: 'AGE'

No gene related to 'AGE'.

Table S2.  Basic characteristics of clinical feature: 'AGE'

AGE Mean (SD) 66.58 (11)
  Significant markers N = 0
Clinical variable #3: 'GENDER'

2 genes related to 'GENDER'.

Table S3.  Basic characteristics of clinical feature: 'GENDER'

GENDER Labels N
  FEMALE 37
  MALE 25
     
  Significant markers N = 2
  Higher in MALE 1
  Higher in FEMALE 1
List of 2 genes differentially expressed by 'GENDER'

Table S4.  Get Full Table List of 2 genes differentially expressed by 'GENDER'

T(pos if higher in 'MALE') ttestP Q AUC
RNASEH2C 5.84 7.272e-07 0.0126 0.8822
KIF4B -5.34 2.092e-06 0.0361 0.8584

Figure S1.  Get High-res Image As an example, this figure shows the association of RNASEH2C to 'GENDER'. P value = 7.27e-07 with T-test analysis.

Clinical variable #4: 'KARNOFSKY.PERFORMANCE.SCORE'

No gene related to 'KARNOFSKY.PERFORMANCE.SCORE'.

Table S5.  Basic characteristics of clinical feature: 'KARNOFSKY.PERFORMANCE.SCORE'

KARNOFSKY.PERFORMANCE.SCORE Mean (SD) 43.33 (38)
  Score N
  0 1
  60 1
  70 1
     
  Significant markers N = 0
Clinical variable #5: 'HISTOLOGICAL.TYPE'

54 genes related to 'HISTOLOGICAL.TYPE'.

Table S6.  Basic characteristics of clinical feature: 'HISTOLOGICAL.TYPE'

HISTOLOGICAL.TYPE Labels N
  LUNG ACINAR ADENOCARCINOMA 3
  LUNG ADENOCARCINOMA MIXED SUBTYPE 13
  LUNG ADENOCARCINOMA- NOT OTHERWISE SPECIFIED (NOS) 33
  LUNG BRONCHIOLOALVEOLAR CARCINOMA MUCINOUS 3
  LUNG BRONCHIOLOALVEOLAR CARCINOMA NONMUCINOUS 4
  LUNG MICROPAPILLARY ADENOCARCINOMA 1
  LUNG MUCINOUS ADENOCARCINOMA 1
  LUNG PAPILLARY ADENOCARCINOMA 2
  MUCINOUS (COLLOID) ADENOCARCINOMA 2
     
  Significant markers N = 54
List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

Table S7.  Get Full Table List of top 10 genes differentially expressed by 'HISTOLOGICAL.TYPE'

ANOVA_P Q
SPAG8 3.554e-52 6.14e-48
IVD 2.94e-36 5.08e-32
TRPV1 4.462e-22 7.71e-18
PITX3 1.187e-20 2.05e-16
NOD2 3.85e-18 6.65e-14
C17ORF64 3.286e-17 5.68e-13
PIK3CB 4.148e-16 7.17e-12
TRAF3IP1 3.609e-15 6.23e-11
ZRANB1 5.252e-14 9.07e-10
C17ORF85 8.786e-14 1.52e-09

Figure S2.  Get High-res Image As an example, this figure shows the association of SPAG8 to 'HISTOLOGICAL.TYPE'. P value = 3.55e-52 with ANOVA analysis.

Clinical variable #6: 'PATHOLOGY.T'

No gene related to 'PATHOLOGY.T'.

Table S8.  Basic characteristics of clinical feature: 'PATHOLOGY.T'

PATHOLOGY.T Mean (SD) 1.93 (0.75)
  N
  T1 16
  T2 36
  T3 6
  T4 3
     
  Significant markers N = 0
Clinical variable #7: 'PATHOLOGY.N'

No gene related to 'PATHOLOGY.N'.

Table S9.  Basic characteristics of clinical feature: 'PATHOLOGY.N'

PATHOLOGY.N Mean (SD) 0.54 (0.79)
  N
  N0 39
  N1 11
  N2 11
     
  Significant markers N = 0
Clinical variable #8: 'PATHOLOGICSPREAD(M)'

75 genes related to 'PATHOLOGICSPREAD(M)'.

Table S10.  Basic characteristics of clinical feature: 'PATHOLOGICSPREAD(M)'

PATHOLOGICSPREAD(M) Labels N
  M0 44
  M1 2
  MX 14
     
  Significant markers N = 75
List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

Table S11.  Get Full Table List of top 10 genes differentially expressed by 'PATHOLOGICSPREAD(M)'

ANOVA_P Q
LRRC8B 1.36e-10 2.35e-06
FBXO16 7.075e-10 1.22e-05
NOTCH2 1.447e-09 2.5e-05
ZNF563 1.582e-09 2.73e-05
LRRC58 1.711e-09 2.96e-05
MREG 3.227e-09 5.58e-05
GPSM2 3.849e-09 6.65e-05
CRELD2 5.289e-09 9.14e-05
CYP2R1 5.791e-09 1e-04
FAM60A 6.021e-09 0.000104

Figure S3.  Get High-res Image As an example, this figure shows the association of LRRC8B to 'PATHOLOGICSPREAD(M)'. P value = 1.36e-10 with ANOVA analysis.

Clinical variable #9: 'TUMOR.STAGE'

No gene related to 'TUMOR.STAGE'.

Table S12.  Basic characteristics of clinical feature: 'TUMOR.STAGE'

TUMOR.STAGE Mean (SD) 1.73 (0.91)
  N
  Stage 1 32
  Stage 2 13
  Stage 3 12
  Stage 4 2
     
  Significant markers N = 0
Clinical variable #10: 'RADIATIONS.RADIATION.REGIMENINDICATION'

52 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S13.  Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION Labels N
  NO 4
  YES 58
     
  Significant markers N = 52
  Higher in YES 21
  Higher in NO 31
List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S14.  Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

T(pos if higher in 'YES') ttestP Q AUC
UHRF1 -10.25 1.48e-13 2.56e-09 0.9784
FBXO9 8.77 2.436e-12 4.21e-08 0.9224
DMXL1 10.9 1.47e-10 2.54e-06 0.9784
PPA1 7.59 1.989e-09 3.44e-05 0.9052
MYL6 -7.52 3.744e-09 6.47e-05 0.9138
NCAN 6.73 7.701e-09 0.000133 0.8362
ZSCAN2 -6.97 1.387e-08 0.00024 0.875
CIDEC -6.81 1.944e-08 0.000336 0.8233
ACTR1B 7.92 2.248e-08 0.000388 0.9009
MRPL55 6.63 2.423e-08 0.000418 0.8491

Figure S4.  Get High-res Image As an example, this figure shows the association of UHRF1 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 1.48e-13 with T-test analysis.

Clinical variable #11: 'NUMBERPACKYEARSSMOKED'

No gene related to 'NUMBERPACKYEARSSMOKED'.

Table S15.  Basic characteristics of clinical feature: 'NUMBERPACKYEARSSMOKED'

NUMBERPACKYEARSSMOKED Mean (SD) 28.14 (29)
  Significant markers N = 0
Clinical variable #12: 'STOPPEDSMOKINGYEAR'

No gene related to 'STOPPEDSMOKINGYEAR'.

Table S16.  Basic characteristics of clinical feature: 'STOPPEDSMOKINGYEAR'

STOPPEDSMOKINGYEAR Mean (SD) 1987.25 (15)
  Significant markers N = 0
Clinical variable #13: 'TOBACCOSMOKINGHISTORYINDICATOR'

7 genes related to 'TOBACCOSMOKINGHISTORYINDICATOR'.

Table S17.  Basic characteristics of clinical feature: 'TOBACCOSMOKINGHISTORYINDICATOR'

TOBACCOSMOKINGHISTORYINDICATOR Labels N
  CURRENT REFORMED SMOKER FOR < OR = 15 YEARS 13
  CURRENT REFORMED SMOKER FOR > 15 YEARS 20
  CURRENT SMOKER 3
  LIFELONG NON-SMOKER 21
     
  Significant markers N = 7
List of 7 genes differentially expressed by 'TOBACCOSMOKINGHISTORYINDICATOR'

Table S18.  Get Full Table List of 7 genes differentially expressed by 'TOBACCOSMOKINGHISTORYINDICATOR'

ANOVA_P Q
MT1H 5.759e-09 9.95e-05
SERPINE1 7.632e-09 0.000132
WFDC10A 1.814e-08 0.000314
EXOC3L 2.307e-08 0.000399
FAM107A 2.919e-07 0.00504
PRELP 6.162e-07 0.0106
DDR2 7.764e-07 0.0134

Figure S5.  Get High-res Image As an example, this figure shows the association of MT1H to 'TOBACCOSMOKINGHISTORYINDICATOR'. P value = 5.76e-09 with ANOVA analysis.

Clinical variable #14: 'YEAROFTOBACCOSMOKINGONSET'

One gene related to 'YEAROFTOBACCOSMOKINGONSET'.

Table S19.  Basic characteristics of clinical feature: 'YEAROFTOBACCOSMOKINGONSET'

YEAROFTOBACCOSMOKINGONSET Mean (SD) 1961.21 (12)
  Significant markers N = 1
  pos. correlated 1
  neg. correlated 0
List of one gene significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

Table S20.  Get Full Table List of one gene significantly correlated to 'YEAROFTOBACCOSMOKINGONSET' by Spearman correlation test

SpearmanCorr corrP Q
RNF123 0.8688 1.393e-06 0.0241

Figure S6.  Get High-res Image As an example, this figure shows the association of RNF123 to 'YEAROFTOBACCOSMOKINGONSET'. P value = 1.39e-06 with Spearman correlation analysis. The straight line presents the best linear regression.

Methods & Data
Input

  • Expresson data file = MOLECULAR_NONSMOKER.meth.for_correlation.filtered_data.txt

  • Clinical data file = MOLECULAR_NONSMOKER.clin.merged.picked.txt

  • Number of patients = 62

  • Number of genes = 17281

  • Number of clinical features = 14

Survival analysis

For survival clinical features, Wald's test in univariate Cox regression analysis with proportional hazards model (Andersen and Gill 1982) was used to estimate the P values using the 'coxph' function in R. Kaplan-Meier survival curves were plot using the four quartile subgroups of patients based on expression levels

Correlation analysis

For continuous numerical clinical features, Spearman's rank correlation coefficients (Spearman 1904) and two-tailed P values were estimated using 'cor.test' function in R

Student's t-test analysis

For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.test' function in R

ANOVA analysis

For multi-class clinical features (ordinal or nominal), one-way analysis of variance (Howell 2002) was applied to compare the log2-expression levels between different clinical classes using 'anova' function in R

Q value calculation

For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

References
[1] Andersen and Gill, Cox's regression model for counting processes, a large sample study, Annals of Statistics 10(4):1100-1120 (1982)
[2] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)
[3] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[4] Howell, D, Statistical Methods for Psychology. (5th ed.), Duxbury Press:324-5 (2002)
[5] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)
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